Not Applicable.
1. Technical Field of the Invention
This present invention relates to telecommunications processing and more particularly to advanced receiver techniques in a multi-user environment.
2. Background Art
The telecommunications industry has been expanding at an unprecedented growth rate. In particular, the wireless sector, including 3G, wireless local area networks and Bluetooth devices, has grown far beyond expectations and at a much higher rate than the fixed telecommunications counterpart. The ability to access data and communicate anywhere at anytime has enormous potential and commercial value.
The content of the wireless sector is also changing, with more and more data being transmitted, including Internet connectivity and live feeds. The usage involving personal digital assistants (PDA""s) and even smart appliances have created new markets utilizing wireless data communications. And, this wireless phenomenon is not limited to any geographical boundaries, as the growth is occurring around the globe.
Although Code Division Multiple Access (CDMA) or spread spectrum communications has been around for many years, there is an increasing interest in using spread spectrum systems in commercial applications to allow superior quality performance and a greater number of users within a given bandwidth. The digital format of CDMA architecture allows complex processing and high-level algorithms for transmission and reception.
Despite the advancements in wireless transmission and reception, there are still problems related to seamless connectivity, multimedia traffic, battery life, security, and mobility to name a few. In general, wireless channels are subject to well-known problems and there are continuous efforts to improve capacity and quality. One of the growing problems is being able to process multiple users in a given bandwidth.
For example, a base station that processes a number of cellular devices has to receive and transmit data within a certain frequency range. The ability to extract the correct data from a given user is a difficult task, especially when the effects of interference and multipaths are considered. The problem is further complicated when the number of users exceeds the number of dimensions, resulting in an overloaded condition.
In the past, prior art communication systems generally utilized Frequency Division Multiple Access (FDMA) and Time Division Multiple Access (TDMA) methods to achieve channel access. FDMA refers to a communication channel wherein a signal""s transmission power is concentrated into a single radio frequency band. Interference from adjacent channels is limited by the use of band pass filters however for each channel being assigned a different frequency, system capacity is limited by the available frequencies and by limitations imposed by channel reuse.
In TDMA systems, a channel consists of a time slot or frame in a periodic train of time intervals over the same frequency, with a given signal""s energy confined to one of these time slots. Adjacent channel interference is limited by the use of a time gate or other synchronization element that only passes signal energy received at the proper time. The system capacity is limited by the available time slots as well as by limitations imposed by channel reuse, as each channel is assigned a different time slot.
One of the goals of FDMA and TDMA systems is to try and prevent two potentially interfering signals from occupying the same frequency at the same time. In contrast, Code Division Multiple Access (CDMA) techniques allow signals to overlap in both time and frequency. CDMA signals share the same frequency spectrum and in the frequency or time domain, the CDMA signals appear to overlap one another. The scrambled signal format of CDMA eliminates cross talk between interfering transmission and makes it more difficult to eavesdrop or monitor calls therefore providing greater security.
In a CDMA system, each signal is transmitted using spread spectrum techniques. The transmitted informational data stream is impressed upon a much higher rate data stream termed a signature sequence. The bit stream of the signature sequence data is typically binary, and can be generated using a pseudo-noise (PN) process that appears random, but can be replicated by an authorized receiver. The informational data stream and the high bit rate signature sequence stream are combined by multiplying the two bit streams together, assuming the binary values of the two bit streams are represented by +1 or xe2x88x921. This combination of the higher bit rate signal with the lower bit rate data stream is called spreading the informational data stream signal. Each informational data stream or channel is allocated a unique signature sequence.
In operation, a plurality of spread information signals, such as binary phase shift keying (BPSK) or quadrature phase shift keying (QPSK) modulation, modulate a radio frequency (RF) carrier and are jointly received as a composite signal at the receiver. Each of the spread signals overlaps all of the other spread signals, as well as noise-related signals, in both frequency and time. The receiver correlates the composite signal with one of the unique signature sequences, and the corresponding information signal is isolated and despread.
A signature sequence is normally used to represent one bit of information. Receiving the transmitted sequence or its complement indicates whether the information bit is a +1 or xe2x88x921, sometimes denoted xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d. The signature sequence usually comprises N pulses, and each pulse is called a xe2x80x9cchipxe2x80x9d. The entire N-chip sequence, or its complement, depending on the information bit to be conveyed, is referred to as a transmitted symbol.
The receiver correlates the received signal with the complex conjugate of the known signature sequence to produce a correlation value. When a xe2x80x98largexe2x80x99 positive correlation results, a xe2x80x9c0xe2x80x9d is detected, and when a xe2x80x98largexe2x80x99 negative correlation results, a xe2x80x9c1xe2x80x9d is detected.
It should be understood that the information bits could also be coded bits, where the code is a block or convolutional code. Also, the signature sequence can be much longer than a single transmitted symbol, in which case a subsequence of the signature sequence is used to spread the information bit.
Further descriptions of CDMA communications techniques are described in U.S. Pat. No. 5,506,861. This patent describes radiotelephone communication systems, and in particular, receivers for jointly demodulating a plurality of CDMA signals with multipath time dispersion.
The prior art systems do not properly account for the real world mobile communication signals that suffer from signal degradation such as interference and multipath problems. The systems of the prior art generally tended to make assumptions that all other interferers and multipaths were additive white Gaussian noise. However, this assumption is not accurate for co-channel interference and multipaths.
Multipath dispersion occurs when a signal proceeds to the receiver along not one but many paths so that the receiver encounters echoes having different and randomly varying delays and amplitudes. Co-channel interference refers to signals received from other users either directly or reflected. The receiver receives a composite signal of multiple versions of the transmitted symbol that have propagated along different paths, called rays, having different relative time. Each distinguishable ray has a certain relative time of arrival at a certain amplitude and phase, and as a result, the correlator outputs several smaller spikes. RAKE receivers are well known in the art and attempt to xe2x80x98rakexe2x80x99 together all the contributions to detect the transmitted symbol and recover the information bit.
Conventional RAKE receivers provide satisfactory performance under ideal conditions, however, the signature sequence must be uncorrelated with time shifted versions of itself as well as various shifted versions of the signature sequences of the other CDMA signals. If one received signal corresponding to the signature sequence of interest has a non-negligible cross correlation with the received signal originating from another transmitter, then the value measured at the receiver, e.g. the correlation value for the signal of interest, is corrupted. In other words, the correlation computed at the receiver that would be used to decode a particular signal of interest is overwhelmed by an interfering signal, this is referred to as the near-far problem. The interference caused by an echo of one transmitted symbol overlapping with the next transmitted symbol must also be negligible.
If this is not true, the transmitted symbols interfere with past and future transmitted symbols, which is commonly referred to as intersymbol interference (ISI). In actuality, performance is degraded by other signal interference and ISI. There has been much research to address signal interference with known multipath time dispersion. This is termed joint demodulation with no multipath and is further described in S. Verdu, xe2x80x9cMinimum Probability of Error For Asynchronous Gaussian Multiple-Access Channels,xe2x80x9d IEEE Trans. Info. Theory, Vol. IT-32, pp. 85-96, R. Lupas and S. Verdu, xe2x80x9cLinear multiuser detectors for synchronous code-division multiple-access channels,xe2x80x9d IEEE Trans. Inform. Theory, Vol. 35, pp. 123-136, January 1989; and R. Lupas and S. Verdu, xe2x80x9cNear-far resistance of multiuser detectors in asynchronous channels,xe2x80x9d IEEE Trans. Commun., Vol. 38, pp. 496-508, April 1990.
There are a host of approaches for jointly demodulating any set of interfering digitally modulated signals, including multiple digitally modulated signals. Maximum Likelihood Sequence Estimation determines the most likely set of transmitted information bits for a plurality of digital signals without multipath time dispersion. The maximum likelihood joint demodulator is capable, in theory, of accommodating the largest number of interfering signals, but has a prohibitive computational complexity that makes it unrealizable in practice. The decorrelation receiver is another, less computationally complex receiver processing approach that zeroes out or decorrelates the different signals so that they no longer interfere with one another. The decorrelator, as well as virtually every other lower complexity joint demodulator, is not capable of operation when the number of signals is over a set threshold which falls significantly short of the theoretical maximum.
In a real world multi-user system, there are a number of independent users simultaneously transmitting signals. These transmissions have the real-time problems of multi-path and co-channel interference, fading, and dispersion that affect the received signals. As described in the prior art, multiple user systems communicate on the same frequency and at the same time by utilizing parameter and channel estimates that are processed by a multi-user detector. The output of the multi-user detector is an accurate estimation as to the individual bits for an individual user.
Moreover, in an article by Paul D. Alexander, Mark C. Reed, John A. Asenstorfer and Christian B. Schlagel in IEEE Transactions on Communications, vol. 47, number 7, July 1999, entitled xe2x80x9cIterative Multi-User Interference Reduction: Turbo CDMA,xe2x80x9d a system is described in which multiple users can transmit coded information on the same frequency at the same time, with the multi-user detection system separating the scrambled result into interference-free voice or data streams.
Emerging receiver processing procedures allow for huge increases in the utilization of multiple access communications, such as wireless cellular phones. The common problem is that the processing procedures in the receivers are difficult to run in real time. Advanced receiver techniques cover several areas, namely interference suppression (also called multi-user detection), multipath combining and space-time processing, equalization, and channel estimation. These various techniques can be mixed and matched depending upon the circumstances. Proper signal processing of transmitter and receiver yield a far greater potential than current systems.
Multi-user detection (MUD) refers to the detection of data in non-orthogonal multiplexes. MUD processing increases the number of bits available per chip or signaling dimension for systems having interference limited systems. A MUD receiver jointly demodulates co-channel interfering digital signals.
Optimal MUD based on the maximum likelihood sequence estimator operates by comparing the received signal with the entire number of possibilities that could have resulted, one for each bit or symbol epoch. Unfortunately, this processing is a computationally complex operation and it is not possible to accomplish in a real-time environment. Thus for those multi-user detectors that examine the entire space, real-time operation is often elusive.
In general, optimal MUD units function by examining a number of possibilities for each bit. However, for multi-user detectors that examine a larger capacity of signal, the computations are complex and time-consuming, thus making real-time operation impossible. Numerous attempts at reliable pruning of the optimal MUD decision process or the use of linear approximation to the replace the optimal MUD have still not produced a workable solution for the real world environment.
There are various multiuser detectors in the prior art, including optimal or maximum likelihood MUD, maximum likelihood sequence estimator for multiple interfering users, successive interference cancellation, TurboMUD or iterative MUD, and various linear algebra based multi-user detectors such as all of those detailed in the well-known text xe2x80x9cMultiuser Detectionxe2x80x9d by Sergio Verdu. In basic terms, turbodecoding refers to breaking a large processing process into smaller pieces and performing iterative processing on the smaller pieces until the larger processing is completed. This basic principle was applied to the MUD.
There are known problems in these prior art concepts. Linear Algebra based MUD (non-iterative) and successive interference cancellation fails for cases of overloaded multiple access systems. One example of overloading is where the number of simultaneous users is doubled relative to existing state of the art. Even for underloaded multiple access systems, the performance of non-iterative MUD and successive interference cancellation degrades significantly as the number of users increases, while the computation complexity of the optimal MUD increases significantly as the number of users increases. The computing problems are so extreme that it requires extensive and expensive hardware as well as complex processing. Moreover, an unreasonable delay would be required to decode each bit or symbol rendering such a system useless in practice.
Reduced complexity approaches based on tree-pruning help to some extent to eliminate the proper bit combination from consideration (i.e. prune the proper path in the decision tree) based on information from an unreliable bit estimate.
The M-algorithm is a pruning process that limits the number of hypotheses extended to each stage to a fixed tree width and prunes based on ranking metrics for all hypotheses and retaining only the M most likely hypotheses. The T-algorithm prunes hypotheses by comparing the metrics representing all active hypotheses to a threshold based on the metric corresponding to the most-likely candidate. Performance of M-algorithm based MUD degrades as the parameter M is decreased, but M governs the number of computations required. Similar effects are seen for other tree-pruning based MUD (T-algorithm, etc). To combat improper pruning, basic tree-pruning must ensure that M is xe2x80x9clarge enoughxe2x80x9d, and therefore still encounters increased complexity for acceptable performance levels when the number of interfering signals and/or ISI lengths are moderate to large.
As an illustration of the M-algorithm as a tree-pruning algorithm, consider a tree made up of nodes and branches. Each branch has a weight or metric, and a complete path is a sequences of nodes connected by branches between the root of the tree and its branches. When applied as a short cut to the optimal MUD, each branch weight is a function of the signature signal of a certain transmitter, the possible bit or symbol value associated with that transmitter at that point in time, and the actual received signal which includes all the signals from all the interfering transmissions. The weight of each path is the sum of the branch metrics in a complete path. The goal of a tree searching algorithm is to try to find the complete path through a tree with the lowest metric. With the present invention the metrics of multiple complete paths are not calculated. Rather, the metrics of individual branches in a tree are calculated in the process of locating one complete path through the tree and thereby defines one unknown characteristic of each of the co-channel, interfering signals needed to decode the signals.
A MUD algorithm within the TurboMUD system determines discrete estimates of the transmitted channel symbols, with the estimates then provided to a bank of single-user decoders (one decoder for each user) to recover the input bit streams of all transmitted signals.
Two general types of multi-user detectors within the TurboMUD system are possible, namely those that provide hard outputs, which are discrete values, and those that provide soft outputs, which indicate both the discrete estimate and the probability that the estimate is correct.
However, single-user decoders operating on hard values, or discrete integers, have unacceptable error rates when there is a large amount of interference. The reason is that discrete integers do not provide adequate confidence values on which the single-user decoder can operate. These decoders operate better on so-called soft inputs in which confidence values can range from xe2x88x921 to 1, such as for instance 0.75 as opposed to being either xe2x88x921 or +1.
In an attempt to provide soft values that can then be utilized by a single-user decoder, the multi-user detector can generate these soft values. However the processing takes an inordinate amount of time. As a result, these systems do not produce real-time results. Since single-user decoders operate best on soft values, it is often times the case that the computational complexity for a robust MUD capable of generating these soft values makes it impossible to get a real-time result.
In an attempt to provide real-time performance by reducing the computational complexity of an iterative multi-user detector that can produce soft values, the prior art suggests algorithms for examining less than the total number of possibilities for each of the bits of data that are coming in from the multiple users. The xe2x80x9cshortcutsxe2x80x9d taken by this reduced complexity approach cause errors and combating these errors by increasing the number of iterations of the system completely nullifies any advantage.
Thus, while the MUD unit can generate soft values within the iterative cycle of the TurboMUD, the entire detection system is slowed down in generating these soft values. It should be appreciated that these soft values, rather than being integers which would be considered to be hard values, are real numbers, which in effect, permit a single user decoder to better error correct the output of the multi-user detector and thereby provide a more robust bit stream that will faithfully represent the original input for a given user.
Moreover, when dealing with hand-held communications units such as wireless handsets, the amount of processing within the device is limited, directly limiting the amount of computational complexity that is allowed. In order to provide real-time performance both at a cell site and the handset, it therefore becomes important to be able to reduce the amount of computational complexity and processing time so as to achieve realtime performance.
A further description of a TurboMUD system is described in an article by Paul D. Alexander, Mark C. Reed, John A. Asenstorfer and Christian B. Schlagel in IEEE Transactions on Communications, vol. 47, number 7, July 1999, entitled xe2x80x9cIterative MultiUser Interference Reduction: Turbo CDMAxe2x80x9d, wherein multiple users transmit coded information on the same frequency at the same time.
The growing demand for radio communications raises the need to optimize the performance while maximizing the capacity of wireless communications systems. To optimize performance in a multi-user environment either interference must be eliminated (convention), or the number of interfering signals must be kept below a pre-determined number (virtually all non-optimum MUD techniques) which is typically far less than multiuser theory would allow. Existing approaches fail to address all of these problems. What is needed is an efficient signal processing technique to improve the quality and spectral efficiency of wireless communications and better techniques for sharing the limited bandwidth among different high capacity users. As can be seen, attempts to make real-time processing multi-user processing have been frustrated by complex and sophisticated hardware and processing requirements. What is needed therefore, is a method and apparatus for allowing multiple users to operate in the same channel. Such a system should provide accurate cancellation of interfering signals while reducing complex processing.
The invention is devised in the light of the problems of the prior art described herein. Accordingly it is a general object of the present invention to provide a novel and useful apparatus and technique that can solve the problems described herein.
An object of the invention is to provide a high quality real-time receiver processing for multiple access systems, including overloaded systems, by implementing an iterative cooling enhanced tree-pruned MUD that includes confidence ordering, power-ordering, and a simple voting procedure to produce soft-values. On the first iteration, because confidence values are not yet available to the MUD (or, more correctly, all confidence values are equal), the user indices are ordered according to the received powers. On subsequent iterations, the user indices are ordered according to the confidence values determined by the single user decoders. This allows the MUD detector to operate on the most reliable symbols first, improving the likelihood that the pruning includes the correct path. Unlike prior art devices that tend to reduce or eliminate interferers, the present invention utilizes information from the interferers in order to provide a better likelihood of extracting the transmitted signals.
Thus, the present invention provides a solution to performance degradation in the form of a low-complexity TurboMUD and is aimed at detecting not only underloaded and fullyloaded channels as are virtually all MUD-based systems proposed in the public domain, but is particularly useful against overloaded channels. The voting soft metric production is done for every iteration, wherein the voting operator examines the final surviving states of the tree-pruned MUD algorithm, determines the most likely bit combination from the users via a simple voting procedure, and provides a soft-valued output for the bit combination similar to a probability. The soft-valued outputs may then be passed to a bank of soft-in/soft-out decoders, such as maximum a posteriori (MAP) single user decoders in a TurboMUD application. A pre-processing filter is used that operates for more users than dimensions. Therefore, this invention provides a low-complexity solution that approaches the performance of a full complexity TurboMUD, and operates on overloaded system in which the number of interferers is large.
While the full complexity TurboMUD requires prohibitive computational complexity, it provides a good method for removal of co-channel interference. A reduced complexity Turbo MUD suggested by the prior art still requires significant processing, but provides soft-values that are passed to the single-user decoders resulting in good performance.
Confidence ordering is most effective on the second and subsequent iterations. While effective on a first iteration, power ordering is not as effective as confidence ordering after the first iteration. Voting to produce soft metrics provides a way to simply calculations for soft metrics from hard metrics. The combinations of the three approaches (power ordering, confidence ordering, and soft-metric voting) are used together in the same TurboMUD system, combining their strengths for optimal performance.
Another object of the invention is a system that improves the performance degradation of tree-pruned TurboMUD systems that pass hard values from the MUD to the single-user decoders. The object system determines the symbols for which the majority of survivors agree and provides a soft reliability value to be passed to the single-user decoders. It remains a reduced-complexity approach, with complexity similar to M-algorithm tree-pruning TurboMUD, which means that the system can be implemented in real time.
A further object is a method that reduces the likelihood of improper pruning, thereby allowing for a reduction in the number of branches examined (and, therefore, a reduction in complexity) without negatively impacting performance. For the same complexity, the invention provides for superior performance when compared to other reduced-complexity tree-pruning-based MUD of the prior art.
Additional objects of the invention include making the system of sufficiently low-complexity that it can be implemented in real time. The present invention is compatible with overloaded systems as well as under and fully loaded, because it allows for a front-end filter that will operate well in an overloaded environment. This filter further improves the performance of the tree-pruning process of the MUD. The improved performance and low complexity of the present apparatus give service providers an apparatus that can allow more active transmitters (paying customers, users, phones, devices, etc.) without requiring more bandwidth or compromising performance.
This new method may be used to replace existing receivers without any modification to the transmitters, thereby allowing service providers to offer improved performance without changing the signaling method. For example, cellular phones can still operate with the additional features added to the base station or tower.
The present invention is an improvement on a multiuser detection processing procedure that, without causing degradation in quality of service or decreasing the total throughput, will allow for real time implementation in receivers designed for typical and high data rate multiple access communication. Specifically, the problem solved by this invention is the high computational complexity required by the tree-pruned iterative MUD to avoid the degraded performance caused by early incorrect pruning of the decision tree. In addition, this invention solves the problem of increased complexity typically needed to produce soft-values within the TurboMUD.
The subject of the invention disclosed in this application does not require that the signals correspond to any particular multiple access scheme or even that they are all of the same type, or come from a wireless system. For example, the present invention operates in the same manner on any set of digitally modulated interfering signals to include cellular CDMA systems, TDMA systems, FDMA systems, storage medium, wired MA systems such a cable modems, wireless local area network systems, or yet undetermined systems. For example, Spatial Division Multiple Access (SDMA) is generally a satellite communications technique that optimizes the use of radio spectrum and minimizes system cost by taking advantage of the directional properties of dish antennas and frequency reuse, and benefits from the bit processing described herein. The only requirement for viable operation of the present invention is that each signal source produces a signal with the information digitally modulated using a signature pulse or finite duration signal of some sort. While CDMA is described for illustrative purposes to explain the invention, the specific example of CDMA is merely for ease of understanding. The present invention is directed to any other form of digital communication or signal storage methods by simply replacing the words in the CDMA discussions xe2x80x9csignature sequencexe2x80x9d with xe2x80x9csignature signalxe2x80x9d or xe2x80x9csignature pulsexe2x80x9d and replacing the words xe2x80x9cCDMA signalxe2x80x9d with xe2x80x9cdigitally modulated signalxe2x80x9d.
In summary, the described system provides real-time performance for iterative multi-user detectors, such as TurboMUDs, which are used to separate simultaneous transmissions on the same frequency, by permitting the MUD to use a less computationally intense, fast-processing algorithm and to correct for errors caused by the fast processing. In order to reduce the errors, a power confidence order and voting system are coupled to the input and output of the multi-user detector within the iterative system.
Yet a further object is to decode co-channel, interfering signals at a receiver with a tree based on a decoding algorithm wherein on a first iteration strongest received signal as determined by a parameter estimation unit are assigned in descending order of signal strength. By a first power ordering, a low complexity suboptimal search of the tree will be more likely to report the correct answer. Subsequent iterations utilize confidence ordering to create a higher likelihood of maintaining the correct path when computing subsequent tree decisions.
A further feature of the present invention is that it works equally well using mixed rate communication systems such as IS95, wherein the user chooses the transmission rate. The parameter estimator that handles the differing transmission rates passes along the information to the present system.
An object of the invention is an advanced receiver apparatus for processing signals from multiple users with interfering signals, comprising an ordering unit for ordering users indices, wherein on a first iteration ordering is based on received signal power, and wherein on subsequent iterations ordering is based on confidence values. A multi-user detector coupled to the ordering unit producing a plurality of surviving states. A voting unit coupled to the multi-user detector for processing the surviving states and generating a set of soft estimates of channel symbols. A decoder section coupled to the voting unit and the multi-user detector, wherein the decoder section processes the soft estimates of channel symbols to produce a final output on a final iteration, and wherein the decoder produces the confidence values for intermediate iterations.
A further object of the advanced receiver apparatus comprises a parameter estimation unit coupled to the ordering unit and the multi-user detector for determining and storing various parameters associated with each of the interfering signals present in the received signal. Also, wherein the decoder section is a bank of soft input soft output (SISO) decoders, and wherein the SISO decoders may be selected from the group comprising: maximum a posteriori (MAP) decoders and soft-output Viterbi algorithm (SOVA) decoders. A further object is where the multi-user detector uses an algorithm selected from the group comprising an M-algorithm, T-algorithm, MT-algorithm, and tree pruned versions of the MAP, Log-MAP, and Max-Log MAP. Also, wherein the filter is selected from the group comprising a whitening matched filter, a bank of matched filters, and any bank of orthogonal filters that span the space defined by the collection of interfering signals.
A further object of the advanced receiver apparatus comprises a means for determining the final iteration, wherein the means is a fixed number of iterations or an allowable difference between previous confidence values and current confidence values.
An object of the invention is a method for processing a plurality of receiver signals from multiple users, comprising the steps of processing the receiver signals in a front end to generate a digital signal, performing parameter estimation of the digital signal, ordering instructions for instructing the tree in the MUD, wherein the ordering is a power ordering on a first iteration, and confidence ordering on subsequent iterations, detecting a plurality of solutions by maintaining multiple surviving paths each one corresponding to a complete set of bit streams, one bit stream for each interfering signal, voting on the survivors to generate a single set of a soft-valued outputs, decoding the soft-valued outputs to form a set of confidence values, repeating the steps of confidence ordering, detecting, voting, and decoding until a final state is obtained, and outputting data estimates corresponding to a set of data bit streams, one bit stream for each interfering signal.
A final object of the invention is a receiver system for processing signals from multiple users with interfering signals, comprising a front end unit for receiving and processing incoming receptions, with a parameter estimator unit coupled to the front end unit for processing the receptions. There is a filter section coupled to the parameter estimation unit and an ordering unit coupled to the filter section for ordering users indices, wherein on a first iteration ordering is based on received signal power, and wherein on subsequent iterations ordering is based on confidence values. There is a multi-user detector coupled to the ordering unit producing a plurality of surviving states with a voting unit coupled to the multi-user detector for processing the surviving states and generating a set of soft estimates of channel symbols. A decoder section is coupled to the voting unit and the multi-user detector, wherein the decoder section processes the soft estimates of channel symbols to produce a final output on a final iteration, and wherein the decoder produces the confidence values for intermediate iterations.
Still other objects and advantages of the present invention will become readily apparent to those skilled in this art from the following detailed description, wherein we have shown and described only a preferred embodiment of the invention, simply by way of illustration of the best mode contemplated by us on carrying out our invention. As will be realized, the invention is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the invention.